ProPheno: An online dataset for completely characterizing the human protein-phenotype landscape in biomedical literature

Morteza Pourreza Shahri, Indika Kahanda
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Abstract

Identifying protein-phenotype relations is of paramount importance for applications such as uncovering rare and complex diseases. One of the best resources that captures the protein-phenotype relationships is the biomedical literature. In this work, we introduce ProPheno, a comprehensive online dataset composed of human protein/phenotype mentions extracted from the complete corpora of Medline and PubMed. Moreover, it includes co-occurrences of protein-phenotype pairs within different spans of text such as sentences and paragraphs. We use ProPheno for completely characterizing the human protein-phenotype landscape in biomedical literature. ProPheno, the reported findings and the gained insight has implications for (1) biocurators for expediting their curation efforts, (2) researches for quickly finding relevant articles, and (3) text mining tool developers for training their predictive models. The RESTful API of ProPheno is freely available at http://propheno.cs.montana.edu.
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ProPheno:一个完整描述生物医学文献中人类蛋白质表型景观的在线数据集
确定蛋白质表型关系对于发现罕见和复杂疾病等应用至关重要。捕获蛋白质-表型关系的最佳资源之一是生物医学文献。在这项工作中,我们介绍了ProPheno,这是一个综合的在线数据集,由从Medline和PubMed的完整语料库中提取的人类蛋白质/表型提及组成。此外,它还包括蛋白质-表型对在句子和段落等不同文本范围内的共现。我们使用ProPheno来完全表征生物医学文献中的人类蛋白质表型景观。ProPheno,报告的发现和获得的见解对(1)生物馆长加快他们的策展工作,(2)快速找到相关文章的研究,以及(3)文本挖掘工具开发人员训练他们的预测模型具有重要意义。ProPheno的RESTful API可在http://propheno.cs.montana.edu免费获得。
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